AI Can Estimate an Area's Obesity Levels by Analyzing Its Buildings

Researchers at the University of Washington trained an artificial intelligence algorithm to find the relationship between a city's infrastructure and obesity levels using satellite and Google Street View images. The algorithm was trained using more than 150,000 satellite images of six cities, as well as 96 categories of points of interest such as grocery stores and pet shops, which were included because they could have an effect on the activity of a neighborhood.

The algorithm, correlated with obesity rates from each city, found that areas with more green spaces to walk and more spacing between buildings had lower obesity rates. Further validation tests showed that the algorithm found a link between the number of buildings and green space and obesity, not just wealth, which can also be a factor.